2000
DOI: 10.1007/bf02294963
|View full text |Cite
|
Sign up to set email alerts
|

Kriging methodology for regional economic analysis: Estimating the housing price in Albacete

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
13
0

Year Published

2009
2009
2023
2023

Publication Types

Select...
9
1

Relationship

0
10

Authors

Journals

citations
Cited by 27 publications
(13 citation statements)
references
References 6 publications
0
13
0
Order By: Relevance
“…Kriging and its technical and scienti c applications are widely discussed in literature, and the possibilities o ered by kriging methods are the subject of an ongoing debate [1,3,8,10,16]. The use of kriging in spatial analysis of property transaction prices has also been described in detail by various authors [2,12,15].…”
Section: Methodsmentioning
confidence: 99%
“…Kriging and its technical and scienti c applications are widely discussed in literature, and the possibilities o ered by kriging methods are the subject of an ongoing debate [1,3,8,10,16]. The use of kriging in spatial analysis of property transaction prices has also been described in detail by various authors [2,12,15].…”
Section: Methodsmentioning
confidence: 99%
“…The possibilities offered by geostatistical methods in market analyses have been discussed by MARTINEZ et al (2000), CHICA-OLMO et al (2007, 2013, KULCZYCKI and LIGAS (2007), CICHOCIŃSKI (2009), MONTERO et al (2009), andCOLAKOVIC andVUCETIC (2012). Geostatistical methods create various possibilities in spatial analyses of transaction data, but they cannot always be used due to the adopted assumptions and the imperfect nature of the real estate market.…”
Section: Geostatistical Methodsmentioning
confidence: 99%
“…Kriging is an interpolation technique of which the surrounding measured values are weighted to obtain a predicted value for an un-sampled location. It has been found that this technique has great advantages to analyze complex spatial land price distribution [42][43][44]. Equation (3) illustrates that the predicted value is a function of known values and their weights.…”
Section: Spatial Distribution Modelmentioning
confidence: 99%